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    Title: 治癒設限資料在變係數線性轉換模型的研究
    Other Titles: Varying Coefficient Transformation Cure Models with Censored Data
    Authors: 陳蔓樺
    Contributors: 淡江大學統計學系
    Keywords: 曲線估計;最大概似估計法;平滑曲面;治癒模型
    Curve estimation;Maximum likelihood estimation;Spline smoothing;Cure Rate;Transformation Models
    Date: 2013-08
    Issue Date: 2015-04-21 13:53:58 (UTC+8)
    Abstract: 一般所有存活分析中都是假設事件時間是易感受性,也就是假設每事件必然發生。 在臨床試驗中,這樣的假設對長期存活資料並不適當。在本計畫中,我們將針對事件未 必發生(不易感受性)及存在變係數問題研究探討,更進一步建立線性轉換治癒模型。我 們提出平滑曲面下的最大概似估計量,並證明其一致性與收斂性。期模擬研究結果能與 理論相對應。
    Varying Coefficient Transformation Cure Models with Censored Data The phenomenon of disease may be completely eliminated, that is a significant fraction of patients can be cured; also, the phenomenon of covariates may be time-varying. The method considered in this present paper applies to covariates measured to time-varying covariates is also possible as long as the covariates are ancillary or external with transformation cure models. A maximum likelihood method with spline smoothing is proposed and the estimators, under some regularity conditions, are proved to be consistent and asymptotically normal. A simulation study is presented to show that the proposed method performs well with finite sample and is easy to use in practice.
    Appears in Collections:[統計學系暨研究所] 研究報告

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